Biology subjects

Lucas, L. K.

Publications and source records attributed to Lucas, L. K..

6 recordsLinked to original sources

bioRxiv2026

Genomic forecasts of maladptation in Lycaeides butterflies

Genomic forecasting approaches based on genotype-environment associations (GEAs) are increasingly used to estimate genomic offsets (GOs), which predict population maladaptation and extinction risk under current or future climatic conditions. Despite their widespread use, only a subset of studies have evaluated how accurately GOs predict (mal)adaptation, limiting their interpretation and application in policy and management. Here, we used GEA analyses to estimate GOs for past, present, and future climates in Lycaeides butterflies, focusing on the causes of variation in GOs among populations and their relationships with demographic parameters inferred from population genomic data. Using multivariate linear regression and genotyping-by-sequencing data from 42 Lycaeides populations (922 butterflies), we found that mean annual temperature, cumulative annual precipitation, and hybridization history together explained 47.6% of variation in genome-wide allele frequencies. Genomic offsets differed substantially among populations and across past, present, and future climates, with evidence for increasing maladaptation under more distant future climate scenarios. We found no relationship between GOs for present climates and contemporary effective population size. In contrast, genetic diversity, which reflects long-term effective population size, and local rates of gene flow together explained 27.3% of variation in contemporary GOs. Populations with higher genetic diversity and more gene flow exhibited lower GOs, consistent with the hypothesis that genetic diversity enhances adaptive capacity and that gene flow may introduce adaptive alleles. Overall, our results support the utility of GO predictions, particularly when validated with independent measures of adaptation, while cautioning against simplistic interpretations of GO as a direct measure of maladaptation in conservation and management contexts.

evolutionary biology↗

bioRxiv2025

Admixture in a butterfly species complex creates a genomic mosaic of ancestry with distinct histories for different chromosomes

Hybridization and admixture give rise to populations with mosaic genomes composed of ancestry segments with distinct origins and histories. Despite a growing number of documented cases of admixture in nature, relatively little is known about how mosaic patterns of ancestry vary simultaneously across the genome and among multiple populations or lineages of hybridizing species. Here, using pooled whole-genome sequence data from more than 20 populations representing three nominal species and multiple admixed or taxonomically ambiguous populations, we show that widespread admixture in Lycaeides butterflies has resulted in distinct evolutionary histories within and among chromosomes, with the most notable differences between the autosomes and the Z sex chromosome. Many populations exhibit substantial evidence of mixed ancestry on the autosomes, whereas the Z chromosome shows a more tree-like evolutionary history. In some cases, the predominant ancestry of the autosomes and the Z chromosome differ. We also find evidence of variation in ancestry within chromosomes, though this appears more idiosyncratic. We also show that differences in autosomal versus Z-chromosome ancestry have the potential to shape ecologically important trait variation. Specifically, using genome-wide association mapping, we demonstrate that wing-pattern elements--traits known to influence mate preference--are affected by genetic variants on both the autosomes and the Z chromosome. In sum, our results show that different chromosomes can exhibit distinct evolutionary histories, with the Z chromosome suggesting more discrete evolutionary lineages or species than the autosomes. These findings have implications both for our basic understanding of species and species boundaries and for how we view the sources of genetic and phenotypic variation that fuel ongoing evolutionary change.

evolutionary biology↗

bioRxiv2024

Extensive admixture among karst-obligate salamandersreveals evidence of recent divergence and gene exchangethrough aquifers

Karst ecosystems often contain extraordinary biodiversity, but the complex underground aquifers of karst regions present challenges for assessing and conserving stygobiont diversity and investigating their evolutionary history. We examined the karst-obligate salamanders of the Eurycea neotenes species complex in the Edwards Plateau region of central Texas using population genomics data to address questions about population connectivity and the potential for gene exchange within the underlying aquifer system. The Eurycea neotenes species complex has historically been divided into three nominal species, but their status, and spatial extent of species ranges, have remained uncertain. We discovered evidence of extensive admixture within the species complex and with adjacent lineages. We observed relatively low levels of differentiation among all sampling localities which supports the hypothesis of recent divergence. Nominal taxonomy, aquifer region and geography accounted for a modest amount of the overall population genomic variation, but these predictors were largely collinear and difficult to disentangle. Importantly, the taxonomy of the three nominal species does not reflect the admixture apparent in clustering analyses. Inference of migration events revealed a complex pattern of gene exchange, suggesting that Eurycea salamanders have a dynamic history of dispersal through the aquifer system. These results highlight the need for greater understanding of how stygobiont populations are connected via dispersal and gene exchange through karst aquifers.

evolutionary biology↗

bioRxiv2022

Additive genetic effects in interacting species jointly determine the outcome of caterpillar herbivory

Plant-insect interactions are common and important in basic and applied biology. Trait and genetic variation can affect the outcome and evolution of these interactions, but the relative contributions of plant and insect genetic variation and how these interact remain unclear and are rarely subject to assessment in the same experimental context. Here we address this knowledge gap using a recent host range expansion onto alfalfa by the Melissa blue butterfly. Common garden rearing experiments and genomic data show that caterpillar performance depends on plant and insect genetic variation, with insect genetics contributing to performance earlier in development and plant genetics later. Our models of performance based on caterpillar genetics retained predictive power when applied to a second common garden. Much of the plant genetic effect could be explained by heritable variation in plant phytochemicals, especially saponins, peptides, and phosphatidyl cholines, providing a mechanistic understanding of variation in the species interaction. We find evidence of polygenic, mostly additive effects within and between species, with consistent effects of plant genotype on growth and development across multiple butterfly species. Our results inform theories of plant-insect coevolution and the evolution of diet breadth in herbivorous insects and other host-specific parasites. Teaser summaryThe combined, additive effects of plant and insect genetic variation explain Melissa blue caterpillar growth and development on alfalfa plants.

genomics↗

bioRxiv2021

Genomic time-series data show that gene flow maintains high genetic diversity despite substantial genetic drift in a butterfly species

Effective population size affects the efficacy of selection, rate of evolution by drift, and neutral diversity levels. When species are subdivided into multiple populations connected by gene flow, evolutionary processes can depend on global or local effective population sizes. Theory predicts that high levels of diversity might be maintained by gene flow, even very low levels of gene flow, consistent with species long-term effective population size, but tests of this idea are mostly lacking. Here, we show that Lycaeides butterfly populations maintain low contemporary (variance) effective population sizes (e.g., [~]200 individuals) and thus evolve rapidly by genetic drift. Contemporary effective sizes were consistent with local census populations sizes. In contrast, populations harbored high levels of genetic diversity consistent with an effective population size several orders of magnitude larger. We hypothesized that the differences in the magnitude and variability of contemporary versus long-term effective population sizes were caused by gene flow of sufficient magnitude to maintain diversity but only subtly affect evolution on generational time scales. Consistent with this hypothesis, we detected low but non-trivial gene flow among populations. Furthermore, using population-genomic time-series data, we documented patterns consistent with predictions from this hypothesis, including a weak but detectable excess of evolutionary change in the direction of the mean (migrant gene pool) allele frequencies across populations, and consistency in the direction of allele frequency change over time. The documented decoupling of diversity levels and short-term change by drift in Lycaeides has implications for our understanding of contemporary evolution and the maintenance of genetic variation in the wild.

evolutionary biology↗

bioRxiv2017

The predictability of genomic changes underlying a recent host shift in Melissa blue butterflies

Despite accumulating evidence that evolution can be predictable, studies quantifying the predictability of evolution remain rare. Here, we measured the predictability of genome-wide evolutionary changes associated with a recent host shift in the Melissa blue butterfly (Lycaeides melissa). We asked whether and to what extent genome-wide patterns of evolutionary change in nature could be predicted (1) by comparisons among instances of repeated evolution, and (2) from SNP x performance associations in a lab experiment. We delineated the genetic loci (SNPs) most strongly associated with host use in two L. melissa lineages that colonized alfalfa. Whereas most SNPs were strongly associated with host use in none or one of these lineages, we detected a ~two-fold excess of SNPs associated with host use in both lineages. Similarly, we found that host-associated SNPs in nature could also be partially predicted from SNP x performance (survival and weight) associations in a lab rearing experiment. But the extent of overlap, and thus degree of predictability, was somewhat reduced. Although we were able to predict (to a modest extent) the SNPs most strongly associated with host use in nature (in terms of parallelism and from the experiment), we had little to no ability to predict the direction of evolutionary change during the colonization of alfalfa. Our results show that different aspects of evolution associated with recent adaptation can be more or less predictable, and highlight how stochastic and deterministic processes interact to drive patterns of genome-wide evolutionary change.

evolutionary biology↗